AI with Papers - Artificial Intelligence & Deep Learning
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All the AI with papers. Every day fresh updates about #DeepLearning #MachineLearning #LLM & #ComputerVision Curated by Alessandro Ferrari | https://www.linkedin.com/in/visionarynet/ #AI #chatGPT
Ko'proq ko'rsatish📈 Telegram kanali AI with Papers - Artificial Intelligence & Deep Learning analitikasi
AI with Papers - Artificial Intelligence & Deep Learning (@ai_deeplearning) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 17 259 obunachidan iborat bo'lib, Texnologiyalar & Aralashmalar toifasida 7 509-o'rinni va Malayziya mintaqasida 2 130-o'rinni egallagan.
📊 Auditoriya ko‘rsatkichlari va dinamika
невідомо sanasidan buyon loyiha tez o‘sib, 17 259 obunachiga ega bo‘ldi.
25 Oktabr, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni 261 ga, so‘nggi 24 soatda esa 2 ga o‘zgardi va umumiy qamrov yuqori darajada qolmoqda.
- Tasdiqlash holati: Tasdiqlanmagan
- Jalb etish (ER): Auditoriya o‘rtacha 16.91% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 7.04% ini tashkil etuvchi reaksiyalarni to‘playdi.
- Post qamrovi: Har bir post o‘rtacha 2 918 marta ko‘riladi; birinchi sutkada odatda 1 216 ta ko‘rish yig‘iladi.
- Reaksiyalar va o‘zaro ta’sir: Auditoriya faol: har bir postga o‘rtacha 16 ta reaksiya keladi.
- Tematik yo‘nalishlar: Kontent framework, object, dataset, tba, depth kabi asosiy mavzularga jamlangan.
📝 Tavsif va kontent siyosati
Muallif resursni shaxsiy fikrni ifoda etish maydoni sifatida ta’riflaydi:
“All the AI with papers. Every day fresh updates about #DeepLearning #MachineLearning #LLM & #ComputerVision
Curated by Alessandro Ferrari | https://www.linkedin.com/in/visionarynet/
#AI #chatGPT”
Yuqori yangilanish chastotasi (oxirgi ma’lumot 26 Oktabr, 2026 da olingan) sababli kanal doimo dolzarb va katta qamrovli bo‘lib qoladi. Analitika auditoriya kontent bilan faol hamkorlik qilishini, uni Texnologiyalar & Aralashmalar toifasidagi muhim ta’sir nuqtasiga aylantirishini ko‘rsatadi.
17 259
Obunachilar
+224 soatlar
+17 kun
+26130 kun
Postlar arxiv
🌵 G-Splatting Controllable Portraits 🌵
👉From monocular/casual video captures, Rig3DGS rigs 3D Gaussian Splatting to enable the creation of re-animatable portrait videos with control over facial expressions, head-pose and viewing direction. Authors: Stony Brook University & #Adobe
👉Review https://t.ly/fq71w
👉Paper https://arxiv.org/pdf/2402.03723.pdf
👉Project shahrukhathar.github.io/2024/02/05/Rig3DGS.html
🪵 HASSOD Object Detection 🪵
👉 HASSOD: fully self-supervised detection and instance segmentation. The new SOTA able to understand the part-to-whole object composition like humans do.
👉Review https://t.ly/66qHF
👉Paper arxiv.org/pdf/2402.03311.pdf
👉Project hassod-neurips23.github.io/
👉Repo github.com/Shengcao-Cao/HASSOD
💥 #Py4AI: 2x speakers, 2x tickets! 💥
✅Doubling the speakers (6 -> 12!)
✅Adding a new track (2 tracks in parallel)
✅Releasing a new batch of 100 tickets!
👉 More: https://t.ly/WmVrM
🏇Bootstrapping TAP 🏇
👉#Deepmind shows how large-scale, unlabeled, uncurated real-world data can improve TAP with minimal architectural changes, via a self-supervised student-teacher setup. Source Code released 💙
👉Review https://t.ly/-S_ZL
👉Paper https://arxiv.org/pdf/2402.00847.pdf
👉Code https://lnkd.in/gyi7Dhkn
🍬 ABS: SOTA collision-free 🍬
👉ABS (Agile But Safe): learning-based control framework for agile and collision-free locomotion for quadrupedal robot. Source Code announced (coming) 💙
👉Review https://t.ly/AYu-Z
👉Paper arxiv.org/pdf/2401.17583.pdf
👉Project agile-but-safe.github.io/
👉Repo github.com/LeCAR-Lab/ABS
🚦(adding) Anything in Any Video🚦🚦
👉 XPeng Motors announced Anything in Any Scene: novel #AI for realistic video simulation that seamlessly inserts any object into an existing dynamic video. Strong emphasis on realism, the objects in the BBs don't exist. Source Code released 💙
👉Review https://t.ly/UYhl0
👉Code https://lnkd.in/gyi7Dhkn
👉Paper https://lnkd.in/gXyAJ6GZ
👉Project https://lnkd.in/gVA5vduD
🚦(adding) Anything in Any Video🚦🚦
👉 XPeng Motors announced Anything in Any Scene: novel #AI for realistic video simulation that seamlessly inserts any object into an existing dynamic video. Strong emphasis on realism, the objects in the BBs don't exist. Source Code released 💙
👉Review https://t.ly/UYhl0
👉Code https://lnkd.in/gyi7Dhkn
👉Paper https://lnkd.in/gXyAJ6GZ
👉Project https://lnkd.in/gVA5vduD
🎉 ADΔER: Event-Camera Suite 🎉
👉ADΔER: a novel/unified framework for event-based video. Encoder / transcoder / decoder for ADΔER (Address, Decimation, Δt Event Representation) video streams. Source code (RUST) released 💙 H/T author: Andrew C. Freeman from University of North Carolina, USA.
👉Review https://t.ly/w5_KC
👉Paper arxiv.org/pdf/2401.17151.pdf
👉Repo github.com/ac-freeman/adder-codec-rs
↘️ SEELE: "moving" the subjects ➡️
👉Subject repositioning: manipulating an input image to reposition one of its subjects to a desired location while preserving the image’s fidelity. SEELE is a single diffusion model to address this novel generative sub-tasks
👉Review https://t.ly/4FS4H
👉Paper https://arxiv.org/pdf/2401.16861.pdf
👉Project https://yikai-wang.github.io/seele/
🥓 RANSAC -> PARSAC (neural) 🥓
👉Neural PARSAC: estimating multiple vanishing points (V), fundamental matrices (F) or homographies (H) at the speed of light! Source Code released 💙
👉Review https://t.ly/r9ngg
👉Paper https://lnkd.in/dadQ4Qec
👉Code https://lnkd.in/dYp6gADd
🍋 Diffutoon: new SOTA video 🍋
👉Diffutoon is a cartoon shading approach, aiming to transform photorealistic videos in anime styles. It can handle exceptionally high resolutions and rapid motions. Source code released!
👉Review https://t.ly/sim2O
👉Paper https://lnkd.in/dPcSnAUu
👉Code https://lnkd.in/d9B_dGrf
👉Project https://lnkd.in/dpcsJcX2
🧠350+ Free #AI Courses by #Google🧠
👉350+ free courses from #Google to become professional in #AI & #Cloud. The full catalog (900+) includes a variety of activity: videos, documents, labs, coding, and quizzes. 15+ supported languages. No excuse.
✅𝐈𝐧𝐭𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧 𝐭𝐨 𝐆𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐯𝐞 𝐀𝐈
✅𝐈𝐧𝐭𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧 𝐭𝐨 𝐋𝐋𝐌𝐬
✅𝐂𝐨𝐦𝐩𝐮𝐭𝐞𝐫 𝐕𝐢𝐬𝐢𝐨𝐧 𝐰𝐢𝐭𝐡 𝐓𝐅
✅𝐁𝐚𝐬𝐞𝐥𝐢𝐧𝐞 𝐃𝐚𝐭𝐚, 𝐌𝐋, 𝐀𝐈
✅𝐈𝐧𝐭𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧 𝐭𝐨 𝐑𝐞𝐬𝐩𝐨𝐧𝐬𝐢𝐛𝐥𝐞 𝐀𝐈
👉Review: https://t.ly/517Dr
👉Full list: https://www.cloudskillsboost.google/catalog?page=1
🐙 Rock-Track announced! 🐙
👉Key Lab of Robotics and System announced Rock-Track, the evolution of Poly-MOT, the previous SOTA in 3D MOT Tracking-By-Detection framework.
👉Review https://t.ly/hC0ak
👉Repo, coming: https://lnkd.in/dtDkPwCC
👉Paper coming
🌋EasyVolcap: Accelerating Neural Volumetric🌋
👉Novel #PyTorch library for accelerating neural volumetric video research: volumetric video capturing, reconstruction & rendering
👉Review https://t.ly/8BISl
👉Paper arxiv.org/pdf/2312.06575.pdf
👉Code github.com/zju3dv/EasyVolcap
🦩 WildRGB-D: Objects in the Wild 🦩
👉#NVIDIA unveils a novel RGB-D object dataset captured in the wild: ~8500 recorded objects, ~20,000 RGBD videos, 46 categories with corresponding masks and 3D point clouds.
👉Review https://t.ly/WCqVz
👉Data github.com/wildrgbd/wildrgbd
👉Paper arxiv.org/pdf/2401.12592.pdf
👉Project wildrgbd.github.io/
👢"Virtual Try-All" by #Amazon 👢
👉#Amazon announces ”Diffuse to Choose”: diffusion-based image-conditioned inpainting for VTON. Virtually place any e-commerce item in any setting.
👉Review https://t.ly/at07Y
👉Paper https://lnkd.in/dxR7nGtd
👉Project diffuse2choose.github.io/
🫧 SAM + Open-Models 🫧
👉Grounded SAM (w/ DINO) as an open-set detector to combine with SAM. This integration enables the detection and segmentation of any regions based on arbitrary text inputs and opens a door to connecting various vision models. It can seamlessly integrate with other Open-World models to accomplish more intricate visual tasks.
👉Review https://t.ly/FwasQ
👉Paper https://arxiv.org/pdf/2401.14159.pdf
👉Code https://github.com/IDEA-Research/Grounded-Segment-Anything
🧪 SUPIR: SOTA restoration 🧪
👉SUPIR is the new SOTA in image restoration; suitable for restoration of blurry objects, defining the material texture of objects, and adjusting restoration based on high-level semantics
👉Review https://t.ly/wgObH
👉Project https://lnkd.in/dPcnBKWm
👉Paper https://lnkd.in/dZPYcUuq
👉Demo coming 🩷 but no code announced :(
🔥Lumiere: SOTA video-gen🔥
👉#Google unveils Lumiere: Space-Time Diffusion Model for Realistic Video Generation. It's the new SOTA, tasks: Text-to-Video, Video Stylization, Cinemagraphs & Video Inpainting.
👉Review https://t.ly/nalJR
👉Paper https://lnkd.in/d-PvrGjT
👉Project https://t.ly/gK8hz
🎭 UltrAvatar: ULTRA-Realistic Avatar 🎭
👉Novel 3D avatar with enhanced fidelity of geometry, and superior quality of physically based rendering (PBR) textures without unwanted lighting.
👉Review https://t.ly/B3BEu
👉Project https://lnkd.in/dkUQHFEV
👉Paper https://lnkd.in/dtEQxrBu
👉Code coming 🩷
